Petri Nets Model Based on Matrix Operation

Abstract

In view of the issue of the single membership grade that exists in the fuzzy Petri nets(FPN), with the combination of the matrix computation and Petri nets theory, the Matrix Operation Petri Nets (MOPN) model is constructed and applied for the representation and reasoning of the knowledge. Firstly the MOPN model is constructed, and applied to the representation of the knowledge, and through the introduction of the inhibition transition arc in the model, the issue of the representation of the negative proposition is solved. Secondly, the MOPN reasoning algorithm is put forward, and by the modification of the transfer rules of the token value after the transitioning and triggering, it has solved the issue of the retention of the fact in the process of reasoning. Finally, the reasoning algorithm is analyzed, and examples are provided to validate the feasibility of the proposed MOPN model and its inference algorithm, the results show that the MOPN is an effective expansion and development of FPN, and its description of the reasoning result is more delicate and comprehensive.